Peyman Milanfar

MDSP Resolution Enhancement Software

This is a Matlab-based software package for resolution enhancement from video,
developed at the Multi-Dimensional Signal Processing (MDSP) research lab at
the University of California at Santa Cruz, led by Peyman Milanfar.

The main objective of this software tool is the implementation of several
superresolution techniques. In particular, the techniques described in [1],
[2], [3], and several references therein are included. The
techniques implemented cover robust methods, dynamic color superresolution
methods, and simultaneous demosaicing and resolution enhancement.

Some specific features of the software package are:

As part of this software package,
motion estimation is done automatically by the program, or independently
estimated motion vectors may be provided by the user.

The user is able to specify the region
of interest to be processed.

A basic tracking algorithm is incorporated
in the program so that if only a certain part of the input images are
important for the user (a car moving in a crowded street), this region
can be tracked and another data sequence containing only that particular
object is produced.

The parameters of the imaging system
(such as the point-spread function) may be specified by the user.

The input image files may be given
as .mat (Matlab data file) or .avi format.

The output generated by the program
can be .mat (Matlab data file) or .avi format.

For purposes of experimentation,
the software package is capable of producing simulated video data for
different imaging scenarios from a single high resolution input image,
with user-controlled parameters.

Examples

Sample results illustrating the performance of our techniques can be viewed here:

Acknowledgements

The work implemented in this software was carried out in collaboration with Prof.
Michael Elad of the Technion CS department. Sina Farsiu is the principal architect of the code, with significant contributions from Dirk Robinson, particularly on the motion estimation algorithms.

This work was supported in part by the National Science Foundation Grant CCR-9984246, US Air Force Grant F49620-03-01-0387, and by the National Science Foundation Science and Technology Center for Adaptive Optics, managed by the University of California at Santa Cruz under Cooperative Agreement No. AST-9876783.